Abstract A102: Differential Gene Expression Overlap as a Predictive Biomarker of CAR T-Cell Therapy Response in Pancreatic Cancer and Lymphoma
Alibeth E. Luna Alvear, Deiver Suarez Gomez, Gustavo Bertran, Mauricio Cabrera, Clara E. IsazaAbstract
Background
& Objectives: CAR T-cell therapy has emerged as a promising cancer treatment, demonstrating remarkable success in hematologic malignancies but less success in solid tumors. Despite its clinical efficacy in certain cancers, predictive biomarkers of response remain limited. This study evaluates whether the degree of coincidence between differentially expressed genes (DEGs) in untreated cancers and post–CAR T therapy expression profiles can serve as a predictive indicator of therapeutic effectiveness.
Methods:
DEG lists from solid (pancreatic cancer) and hematologic (lymphoma) malignancies were contrasted against DEG profiles obtained after CAR T-cell therapy. Publicly available microarray datasets were analyzed using Optimization-Based Analysis of Multiple Arrays (OBAMA). DEG coincidence was quantified and evaluated for its potential association with known clinical outcomes.
Results:
Lymphoma DEGs demonstrated consistently higher overlap with post–CAR T expression profiles compared to pancreatic cancer. In contrast, pancreatic cancer DEGs showed near-zero overlap across multiple comparisons, aligning with the limited clinical success of CAR T therapy in solid tumors. Functional enrichment analysis revealed that pancreatic DEGs were primarily associated with metabolic and ribosomal pathways, suggesting mechanisms related to T-cell exhaustion and immune evasion. Conversely, lymphoma DEGs were enriched in immune activation and complement pathways, reflecting a tumor microenvironment more favorable to CAR T efficacy. Sex-stratified analyses revealed higher DEG overlap in lymphoma across groups, indicating potential sex- and tissue-specific response patterns.
Conclusions:
DEG coincidence emerges as a biological indicator for predicting the effectiveness of CAR T-cell therapy. These findings highlight key molecular differences between solid and hematologic malignancies, supporting the development of gene expression–based predictive metrics for immunotherapy response. Acknowledgment: This project was supported by the NSF Engineering Research Center for Cell Manufacturing Technologies (CMaT).
Citation Format:
Alibeth E. Luna Alvear, Deiver Suarez Gomez, Gustavo Bertran, Mauricio Cabrera, Clara E. Isaza. Differential Gene Expression Overlap as a Predictive Biomarker of CAR T-Cell Therapy Response in Pancreatic Cancer and Lymphoma [abstract]. In: Proceedings of the AACR Conference on Pancreatic Cancer: New Frontiers in Biology and Therapeutic Development; 2026 Sep 25-28; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(18_Suppl_2):Abstract nr A102.